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Record W4401034035 · doi:10.1177/08980101241262922

Transcendental Meditation Enriches Nurses’ Authentic Presence Through Caring for Self and Others

2024· article· en· W4401034035 on OpenAlexaff
Catherine Aquino‐Russell, Jennifer Bonamer, Susan Hartranft, Mary Kutash, Ayesha Johnson

Bibliographic record

VenueJournal of Holistic Nursing · 2024
Typearticle
Languageen
FieldPsychology
TopicMindfulness and Compassion Interventions
Canadian institutionsUniversity of New Brunswick
FundersDavid Lynch Foundation
KeywordsTranscendental meditationMeditationTranscendental numberEmpathyPsychotherapistPsychologySocial psychologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Purpose of Study: Given the enormity of the most recent challenges to clinician well-being, intensified by the pandemic, we decided to explore the influence of Transcendental Meditation ® (TM) ® on the well-being of clinical nurses. The purpose of our study was to use qualitative analysis to enhance our understanding of the experiences of clinical nurses who practiced TM, as viewed through the lens of our conceptual model and Watson's holistic unitary caring science theory. Design and Method: This qualitative study involved a thematic analysis of clinical nurses’ written descriptions following the completion of the TM program during the COVID-19 pandemic. Findings: The nurse participants shared their experiences with the practice of TM as creating present moment focus, leading to enhanced self-care, and development of authentic presence with others. The overall theme uncovered in the analysis is that authentic presence is veritas (truth) in knowing, being, doing, and becoming. Conclusions: The findings were congruent with Watson's unitary caring science theory and provided illumination of the holistic value of TM as a self-care strategy for supporting nurses’ well-being with the goal of retaining nurses in practice. When nurses care for themselves, they are more likely and able to care for others, thus helping them to enjoy their nursing careers.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.408
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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